F. Trujillo

• Universidad de Cádiz

The development of a reliable tool to know the behaviour of stainless steel on localized corrosion is necessary to achieve a proper selection of the material in the structures design. In order to know the behavioural pattern of stainless steel on localized corrosion, a total of 60 samples of austenitic stainless steel were subjected to polarization...

Different artificial intelligent tools have been used to model pitting corrosion behaviour of EN 1.4404 austenitic stainless steel. Samples from this material have been subjected to polarization tests in different chloride solutions using different precursor salts: NaCl and MgCl2. The aim of this work is to compare the results obtained from the dif...

Different classification techniques such as Classification Tree (CT), Discriminant Analysis (DA), K-Nearest Neighbour (KNN) and Back-Propagation Neural Networks (BPNN) have been used to model pitting corrosion behaviour of austenitic stainless steel EN 1.4404. The main purpose is to predict the corrosion status of this material in different environ...

Different methods of classification have been used in this paper to model pitting corrosion behaviour of austenitic stainless steel EN 1.4404. This material was subjected to electrochemical polarization tests in aqueous environment of varying chloride ion concentration (from NaCl solutions), pH values and temperature in order to determine values of...